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Part 1: Document Description
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Citation |
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Title: |
Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach |
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Identification Number: |
doi:10.21979/N9/HOX79X |
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Distributor: |
DR-NTU (Data) |
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Date of Distribution: |
2025-02-28 |
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Version: |
1 |
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Bibliographic Citation: |
Li, Yuanjian; Madhukumar, A. S., 2025, "Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach", https://doi.org/10.21979/N9/HOX79X, DR-NTU (Data), V1 |
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Citation |
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Title: |
Related Data for: Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach |
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Identification Number: |
doi:10.21979/N9/HOX79X |
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Authoring Entity: |
Li, Yuanjian (Nanyang Technological University) |
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Madhukumar, A. S. (Nanyang Technological University) |
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Software used in Production: |
Python |
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Grant Number: |
Competitive Research Programme (Grant Number: NRF-CRP23-2019-0005) |
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Grant Number: |
Future Communications Research & Development Programme (Grant Number: FCP-NTU-RG-2022-014) |
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Distributor: |
DR-NTU (Data) |
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Access Authority: |
Li, Yuanjian |
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Access Authority: |
Li, Yuanjian |
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Depositor: |
Li, Yuanjian |
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Date of Deposit: |
2025-02-27 |
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Holdings Information: |
https://doi.org/10.21979/N9/HOX79X |
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Study Scope |
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Keywords: |
Engineering, Engineering, Terahertz communications, Ultra-massive multiple-input multiple-output systems, Channel estimation, Compressed sensing, Dictionary learning |
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Abstract: |
Python source code associated with the publication titled "Hybrid Near- and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach". These codes can be used to produce simulation figures in this publication. |
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Kind of Data: |
Source code Python |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.1109/TWC.2024.3514141 |
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Bibliographic Citation: |
Li, Y., & Madhukumar, A. S. (2024). Hybrid Near-and Far-Field THz UM-MIMO Channel Estimation: A Sparsifying Matrix Learning-Aided Bayesian Approach. IEEE Transactions on Wireless Communications. |
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Citation |
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Identification Number: |
10356/181807 |
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Bibliographic Citation: |
Li, Y. & Madhukumar, A. S. (2024). Hybrid near- and far-field THz UM-MIMO channel estimation: a sparsifying matrix learning-aided Bayesian approach. IEEE Transactions On Wireless Communications. |
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Label: |
BL_ChannelEstimation.py |
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Notes: |
text/x-python |
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dicLearning.py |
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Notes: |
text/x-python |
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Label: |
Environment.py |
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Notes: |
text/x-python |
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Label: |
main_BLCE_NMSE_vs_pilotLength.py |
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Notes: |
text/x-python |
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main_BLCE_NMSE_vs_SNR.py |
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Notes: |
text/x-python |
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main_unifiedConfig.py |
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Notes: |
text/x-python |
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Label: |
utils.py |
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Notes: |
text/x-python |